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Computers
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e-health Pervasive Wireless Applications and Services (e-HPWAS'22)
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e-health Pervasive Wireless Applications and Services (e-HPWAS'22)

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 13264

Special Issue Editors

Dr. Tayeb Lemlouma

E-Mail Website
Guest Editor
IRISA CNRS Lab, Univ Rennes, IUT de Lannion, 22300 Lannion, France
Interests: context awareness; pervasive and ubiquitous computing; IoT; e-Health; smart and media services in heterogeneous environments; smart content delivery; content-centric
Special Issues, Collections and Topics in MDPI journals
Dr. Yevgeniya Kovalchuk

E-Mail Website
Guest Editor
Advanced Research Computing Centre, University College London, Gower Street, London WC1E 6BT, UK
Interests: artificial intelligence; machine learning; software engineering; embedded systems; software–hardware integration; sensors and wearables; cyber security; mutli-agent systems; healthcare informatics; movement science and movement and art therapy
Special Issues, Collections and Topics in MDPI journals
Dr. Sébastien Laborie

E-Mail Website
Guest Editor
LIUPPA Lab, University of Pau, 64012 Pau, France
Interests: multimedia documents and applications; adaptation and user profiling; semantic web
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Abderrezak Rachedi

E-Mail Website
Guest Editor
Laboratoire d'Informatique Gaspard Monge, Université Gustave Eiffel, 77454 Marne-la-Vallée, France
Interests: computer network; Internet of Things; AIoT: artificial Intelligent of Things; applied cryptography; blockchain
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

e-HPWAS'22 aims at providing optimal, secure, and context-aware e-health systems with the best quality of services (QoS) and user experience (QoE). Applications and services are implemented in wireless environments and architecture with the use of IoT (Internet of Things), big data analysis, and a strong heterogeneity of access technologies, sensors, terminals, user needs analyzers, and services (data, content, live streams, or complex network services).

Emerging e-health services and applications can involve the use of “heavy” content such as multimedia content and streams (e.g., 3D-TV, media conferencing, remote live diagnostics) using conventional e-health devices or terminals such as smart TV sets, home boxes, smartphones, tablets, and new things. The main topics of e-HPWAS are related to e-health care and safety services provided for patients, the elderly, and dependent persons. These services are generally built using different communication technologies for different profiles of people in different contexts and places (e.g., in health institutions, at home, in cities). The provided services should, ideally, be accessible anytime, anywhere, and using any kind of device or platform.

The authors of the IEEE eHPWAS 2022 are encouraged to submit an extended version of their work to this Special Issue of the journal Computers with a minimum of 50% of new content and input. Papers describing advanced prototypes, platforms, techniques, and general surveys for discussing future perspectives and directions are encouraged. Each manuscript will be blind-reviewed by academic editors.

Dr. Tayeb Lemlouma
Dr. Yevgeniya Kovalchuk
Dr. Sébastien Laborie
Prof. Dr. Abderrezak Rachedi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • e-health
  • Internet of Things (IoT)
  • big data analysis, summarization, prediction
  • sensor networks (e.g., BAN, WPAN, etc.)
  • network interoperability
  • security and privacy
  • user acceptance
  • norms for e-Health (e.g., HL7 norms, electronic health information exchange-HIE, Health Record-HER)
  • web norms for e-health (e.g., WebRTC)
  • context models

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Published Papers (4 papers)

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Research

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15 pages, 4736 KiB  
Article
Comparison between an RSSI- and an MCPD-Based BLE Indoor Localization System
by Silvano Cortesi, Christian Vogt and Michele Magno
Computers 2023, 12(3), 59; https://doi.org/10.3390/computers12030059 - 10 Mar 2023
Cited by 4 | Viewed by 3268
Abstract
IPS is a crucial technology that enables medical staff and hospital management to accurately locate and track persons or assets inside medical buildings. Among other technologies, readily available BLE can be exploited to achieve an energy-efficient and low-cost solution. This work presents the [...] Read more.
IPS is a crucial technology that enables medical staff and hospital management to accurately locate and track persons or assets inside medical buildings. Among other technologies, readily available BLE can be exploited to achieve an energy-efficient and low-cost solution. This work presents the design, implementation and comparison of a RSSI-based and a MCPD-based indoor localization system. The implementation is based on a lightweight wkNN algorithm that processes RSSI and MCPD distance data from connection-less BLE Beacons. The designed hardware and firmware are implemented around the state-of-the-art SoC for BLE, the nRF5340 from Nordic Semiconductor. Experimental evaluation with real-time data processing has been evaluated and presented in a 7.3 m × 8.9 m room with furniture and six beacon nodes. The experimental results on randomly chosen validation points within the room show an average error of only 0.50 m for the MCPD approach, whereas the RSSI approach achieved an error of 1.39 m. Full article
(This article belongs to the Special Issue e-health Pervasive Wireless Applications and Services (e-HPWAS'22))
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25 pages, 3925 KiB  
Article
Feasibility and Acceptance of Augmented and Virtual Reality Exergames to Train Motor and Cognitive Skills of Elderly
by Christos Goumopoulos, Emmanouil Drakakis and Dimitris Gklavakis
Computers 2023, 12(3), 52; https://doi.org/10.3390/computers12030052 - 27 Feb 2023
Cited by 6 | Viewed by 3944
Abstract
The GAME2AWE platform aims to provide a versatile tool for elderly fall prevention through exergames that integrate exercises, and simulate real-world environments and situations to train balance and reaction time using augmented and virtual reality technologies. In order to lay out the research [...] Read more.
The GAME2AWE platform aims to provide a versatile tool for elderly fall prevention through exergames that integrate exercises, and simulate real-world environments and situations to train balance and reaction time using augmented and virtual reality technologies. In order to lay out the research area of interest, a review of the literature on systems that provide exergames for the elderly utilizing such technologies was conducted. The proposed use of augmented reality exergames on mobile devices as a complement to the traditional Kinect-based approach is a method that has been examined in the past with younger individuals in the context of physical activity interventions, but has not been studied adequately as an exergame tool for the elderly. An evaluation study was conducted with seniors, using multiple measuring scales to assess aspects such as usability, tolerability, applicability, and technology acceptance. In particular, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to assess acceptance and identify factors that influence the seniors’ intentions to use the game platform in the long term, while the correlation between UTAUT factors was also investigated. The results indicate a positive assessment of the above user experience aspects leveraging on both qualitative and quantitative collected data. Full article
(This article belongs to the Special Issue e-health Pervasive Wireless Applications and Services (e-HPWAS'22))
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15 pages, 2582 KiB  
Article
A Performance Study of CNN Architectures for the Autonomous Detection of COVID-19 Symptoms Using Cough and Breathing
by Meysam Effati and Goldie Nejat
Computers 2023, 12(2), 44; https://doi.org/10.3390/computers12020044 - 17 Feb 2023
Cited by 6 | Viewed by 2215
Abstract
Deep learning (DL) methods have the potential to be used for detecting COVID-19 symptoms. However, the rationale for which DL method to use and which symptoms to detect has not yet been explored. In this paper, we present the first performance study which [...] Read more.
Deep learning (DL) methods have the potential to be used for detecting COVID-19 symptoms. However, the rationale for which DL method to use and which symptoms to detect has not yet been explored. In this paper, we present the first performance study which compares various convolutional neural network (CNN) architectures for the autonomous preliminary COVID-19 detection of cough and/or breathing symptoms. We compare and analyze residual networks (ResNets), visual geometry Groups (VGGs), Alex neural networks (AlexNet), densely connected networks (DenseNet), squeeze neural networks (SqueezeNet), and COVID-19 identification ResNet (CIdeR) architectures to investigate their classification performance. We uniquely train and validate both unimodal and multimodal CNN architectures using the EPFL and Cambridge datasets. Performance comparison across all modes and datasets showed that the VGG19 and DenseNet-201 achieved the highest unimodal and multimodal classification performance. VGG19 and DensNet-201 had high F1 scores (0.94 and 0.92) for unimodal cough classification on the Cambridge dataset, compared to the next highest F1 score for ResNet (0.79), with comparable F1 scores to ResNet for the larger EPFL cough dataset. They also had consistently high accuracy, recall, and precision. For multimodal detection, VGG19 and DenseNet-201 had the highest F1 scores (0.91) compared to the other CNN structures (≤0.90), with VGG19 also having the highest accuracy and recall. Our investigation provides the foundation needed to select the appropriate deep CNN method to utilize for non-contact early COVID-19 detection. Full article
(This article belongs to the Special Issue e-health Pervasive Wireless Applications and Services (e-HPWAS'22))
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Review

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11 pages, 567 KiB  
Review
To Wallet or Not to Wallet: The Debate over Digital Health Information Storage
by Jasna Karacic Zanetti and Rui Nunes
Computers 2023, 12(6), 114; https://doi.org/10.3390/computers12060114 - 28 May 2023
Cited by 6 | Viewed by 2743
Abstract
The concept of the health wallet, a digital platform that consolidates health-related information, has garnered significant attention in the past year. Electronic health data storage and transmission have become increasingly prevalent in the healthcare industry, with the potential to revolutionize healthcare delivery. This [...] Read more.
The concept of the health wallet, a digital platform that consolidates health-related information, has garnered significant attention in the past year. Electronic health data storage and transmission have become increasingly prevalent in the healthcare industry, with the potential to revolutionize healthcare delivery. This paper emphasizes the significance of recognizing and addressing the ethical implications of digital health technologies and prioritizes ethical considerations in their development. The adoption of health wallets has theoretical contributions, including the development of personalized medicine through comprehensive data collection, reducing medical errors through consolidated information, and enabling research for the improvement of existing treatments and interventions. Health wallets also empower individuals to manage their own health by providing access to their health data, allowing them to make informed decisions. The findings herein emphasize the importance of informing patients about their rights to control their health data and have access to it while protecting their privacy and confidentiality. This paper stands out by presenting practical recommendations for healthcare organizations and policymakers to ensure the safe and effective implementation of health wallets. Full article
(This article belongs to the Special Issue e-health Pervasive Wireless Applications and Services (e-HPWAS'22))
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